Supporting Quality Data Systems: Lessons Learned from Early Implementation of Routine Viral Load Monitoring at a Large Clinic in Lilongwe, Malawi
Successful viral load programs rely on the presence of data systems and high quality of patient data. Using a cohort of 49 patients at Partners in Hope, a large, urban HIV clinic in Malawi, we performed a quality improvement assessment of a new viral load program with a focus on accuracy of data collected from patients as well as adherence to Malawi HIV Guidelines in regard to response to elevated viral loads (≥1,000 copies/mL). Data were obtained from three parallel medical record systems to investigate the proportion of patients with a repeat viral load and whether the three data systems agreed in regard to sociodemographic and clinical data. Fewer than 30% of patients had a repeat viral load within six months, as recommended in the Malawi HIV Guidelines. There were significant problems with data agreement across the three parallel databases used for care. Date of birth was consistent for 55.1% (N=27) of patients, while a different date of birth was noted in all three sources for 10.2% of patients (N=5). Viral load data from all three sources agreed for only 2.0% of patients (N=1). For 65.3% (N=32), the viral load from the laboratory did not match the recorded viral load in the electronic or paper record. Scale-up of viral load monitoring must be accompanied by the development of data systems that support workflow from sample collection to lab and back to provider. Education of providers and strategies for data collection with minimal errors can facilitate scale-up of high quality programs.